Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: obtaining a plurality of disparate platforms and a plurality of actions, wherein each action in the plurality of actions can be performed by at least one platform in the plurality of disparate platforms, wherein a platform in the plurality of disparate platforms cannot communicate with a remainder of the plurality of disparate platforms; receiving a natural language request from a user by a groupware platform, wherein the groupware platform is a part of the plurality of disparate platforms; based on the plurality of actions and the plurality of disparate platforms, deciding to send the natural language request from the user to a natural language processing platform, wherein the groupware platform and the natural language processing platform are not configured to communicate to each other; formatting the natural language request into a formatted natural language request accepted by the natural language processing platform; sending the formatted natural language request to the natural language processing platform; interpreting, by the natural language processing platform, the natural language request to identify a user requested action associated with the natural language request; based on the plurality of actions and the plurality of disparate platforms, determining the platform in the plurality of disparate platforms that can perform the user requested action, wherein the platform, the groupware platform and the natural language processing platform are not configured to communicate to each other; formatting the user requested action into a formatted user requested action accepted by the platform; sending the formatted user requested action to the platform; and performing the action.
This invention relates to a system for integrating disparate platforms that cannot communicate directly with each other to execute user requests. The problem addressed is the lack of interoperability between isolated platforms, preventing seamless execution of actions across them. The solution involves a groupware platform receiving a natural language request from a user, which is then processed by a natural language processing (NLP) platform to identify the requested action. Since the groupware and NLP platforms cannot communicate directly, the request is formatted into a compatible format before being sent to the NLP platform. The NLP platform interprets the request and determines which of the disparate platforms can perform the action. The action is then formatted into a compatible format for the target platform and sent to it for execution. The system enables cross-platform action execution without requiring direct communication between the platforms, ensuring interoperability in isolated environments. The invention ensures that actions are correctly interpreted and routed to the appropriate platform, even when the platforms lack native communication capabilities.
2. The method of claim 1 , comprising: receiving a natural language response from the user in response to performing the action; and providing a feedback to the natural language processing platform, wherein the feedback is reinforcing when the natural language response comprises a positive feedback and the feedback is discouraging when the natural language response comprises a negative feedback.
This invention relates to natural language processing (NLP) systems that interact with users and improve based on user feedback. The problem addressed is the lack of adaptive learning in NLP platforms, where systems often fail to refine their responses based on real-time user interactions. The invention provides a method for enhancing NLP systems by incorporating user feedback to adjust future responses dynamically. The method involves receiving a natural language response from a user after the NLP system performs an action, such as generating a response or executing a command. The system then analyzes the user's response to determine whether it contains positive or negative feedback. If the user's response is positive, the system provides reinforcing feedback to the NLP platform, encouraging it to continue or amplify similar actions in the future. Conversely, if the user's response is negative, the system provides discouraging feedback, prompting the NLP platform to modify or avoid repeating the action. This feedback loop enables the NLP system to learn and adapt its behavior based on direct user input, improving accuracy and user satisfaction over time. The method ensures continuous improvement by leveraging real-time user interactions to refine the system's performance.
3. The method of claim 1 , the plurality of disparate platforms comprising the natural language processing platform, an image analysis platform, and a human capital management database.
This invention relates to a system for analyzing and processing data from multiple disparate platforms to generate insights related to human capital management. The system integrates a natural language processing (NLP) platform, an image analysis platform, and a human capital management (HCM) database to extract, analyze, and correlate information from various sources. The NLP platform processes textual data, such as employee communications, performance reviews, and feedback, to identify trends, sentiment, and key insights. The image analysis platform examines visual data, such as employee photos, documents, or surveillance footage, to detect patterns, anomalies, or relevant information. The HCM database stores structured data, including employee records, attendance, compensation, and performance metrics. The system combines these data sources to provide a comprehensive analysis of workforce dynamics, enabling organizations to make data-driven decisions regarding talent management, employee engagement, and operational efficiency. The integration of these platforms allows for cross-referencing and validation of insights, improving the accuracy and relevance of the generated reports. The system may also include machine learning algorithms to predict future trends, identify risks, and recommend actions based on the analyzed data. This approach enhances human resource management by leveraging diverse data sources to gain deeper insights into workforce behavior and performance.
4. The method of claim 1 , the user requested action comprising creating an expense report, or requesting a vacation.
A system and method for automating user-requested actions in a digital workflow environment. The technology addresses inefficiencies in manual task processing by integrating natural language processing (NLP) and automated workflow execution. Users submit requests via text or voice input, which are parsed to identify the action type, relevant parameters, and required approvals. The system validates the request against predefined rules, retrieves necessary data from connected systems, and routes the request through an approval chain if needed. Once approved, the system executes the action, such as generating an expense report or processing a vacation request, and updates relevant databases. The method ensures compliance with organizational policies by enforcing validation checks before execution. The system also supports multi-step workflows, where a single request may trigger multiple dependent actions. For example, a vacation request may automatically adjust team schedules or notify stakeholders. The solution reduces manual intervention, minimizes errors, and accelerates task completion in enterprise environments.
5. The method of claim 1 , said determining the platform comprising: determining the platform that upon performing the user requested action has received a positive feedback more frequently than the remainder of the plurality of disparate platforms.
This invention relates to a system for selecting an optimal platform to perform a user-requested action by analyzing feedback data from multiple platforms. The problem addressed is the inefficiency of manually selecting a platform for executing a task when multiple options exist, each with varying performance or user satisfaction outcomes. The solution involves automatically identifying the platform that has historically received the most positive feedback when performing the same or similar actions. The method first collects feedback data from a plurality of disparate platforms, where each platform has executed the same or similar user-requested actions in the past. Feedback data may include user ratings, success metrics, or other performance indicators. The system then analyzes this data to determine which platform has the highest frequency of positive feedback for the specific action the user intends to perform. The platform with the most favorable feedback history is selected as the optimal choice for executing the requested action. This approach ensures that the platform with the best track record is chosen, improving efficiency and user satisfaction. The method can be applied to various domains, such as software applications, cloud services, or automated task execution systems, where multiple platforms offer similar functionalities.
6. A method comprising: receiving, by a multiplatform management system, a natural language request from a user; interfacing, by the multiplatform management system, with a plurality of disparate platforms including a natural language processing platform, wherein each platform in the plurality of disparate platforms is configured to perform an action in a plurality of actions, said interfacing comprising formatting the natural language request into a formatted natural language request accepted by the natural language processing platform, and forwarding the formatted natural language request to the natural language processing platform; receiving a user requested action from the natural language processing platform; facilitating communication between the plurality of disparate platforms by determining a platform in the plurality of disparate platforms that can perform the user requested action, formatting the user requested action into a formatted user requested action accepted by the platform and sending the formatted user requested action to the platform; and performing the action.
This invention relates to a multiplatform management system that processes natural language requests from users and coordinates actions across multiple disparate platforms. The system addresses the challenge of integrating and managing interactions between different platforms that may not natively communicate with each other, particularly when users submit requests in natural language. The system receives a natural language request from a user and interfaces with multiple platforms, including a natural language processing (NLP) platform. The request is formatted into a structure accepted by the NLP platform and forwarded for interpretation. The NLP platform identifies the user's requested action, which the system then processes by determining which platform in the network can execute the action. The system formats the action into a format compatible with the target platform and sends it for execution. The system ensures seamless communication between platforms, allowing actions to be performed across disparate systems without manual intervention. This approach enables users to interact with multiple platforms using natural language, while the system handles the technical complexities of platform-specific formatting and communication. The invention simplifies cross-platform workflows by abstracting the underlying platform differences, making it easier to perform actions that span multiple systems.
7. The method of claim 6 , comprising: receiving a natural language response from the user in response to performing the action; and providing a feedback to the natural language processing platform, wherein the feedback is reinforcing when the natural language response comprises a positive feedback and the feedback is discouraging when the natural language response comprises a negative feedback.
This invention relates to natural language processing (NLP) systems that interact with users and improve based on user feedback. The problem addressed is the lack of adaptive learning in NLP platforms, where systems often fail to refine their responses based on real-time user interactions. The invention provides a method for enhancing NLP platforms by incorporating user feedback to adjust future interactions dynamically. The method involves receiving a natural language response from a user after the NLP system performs an action, such as generating a response or executing a command. The system then analyzes the user's response to determine whether it contains positive or negative feedback. If the user's response is positive, the system provides reinforcing feedback to the NLP platform, encouraging similar actions in the future. Conversely, if the user's response is negative, the system provides discouraging feedback, prompting the NLP platform to avoid or modify such actions. This feedback loop enables the NLP system to learn and adapt its behavior based on user preferences and satisfaction, improving accuracy and relevance over time. The method ensures continuous improvement by leveraging direct user input, making the NLP platform more responsive and effective in real-world applications.
8. The method of claim 6 , the plurality of disparate platforms comprising the natural language processing platform, an image analysis platform, and a human capital management database.
This invention relates to a system for analyzing and processing data from multiple disparate platforms to generate insights related to human capital management. The problem addressed is the fragmentation of data across different systems, making it difficult to derive comprehensive insights about workforce performance, engagement, and other human capital metrics. The system integrates data from a natural language processing platform, an image analysis platform, and a human capital management database. The natural language processing platform analyzes text-based data, such as employee communications, feedback, and documents, to extract meaningful insights. The image analysis platform processes visual data, such as images or videos, to derive additional insights, such as employee engagement or workplace conditions. The human capital management database stores structured data related to employee records, performance metrics, and other HR-related information. The system combines these disparate data sources to generate a unified analysis, providing a holistic view of workforce dynamics. This integration allows for more accurate predictions, better decision-making, and improved human capital management strategies. The system may also include machine learning models to enhance the accuracy of the insights derived from the combined data. The overall goal is to bridge the gap between different data sources, enabling organizations to make data-driven decisions about their workforce.
9. The method of claim 6 , the user requested action comprising creating a timecard entry, or an active project query.
A system and method for managing time tracking and project data in a collaborative environment. The invention addresses inefficiencies in traditional time tracking systems, which often require manual data entry, lack real-time project visibility, and fail to integrate seamlessly with project management tools. The method involves receiving a user request for an action related to time tracking or project management, such as creating a timecard entry or querying active projects. The system processes the request by accessing a database containing user profiles, project data, and time tracking records. For timecard entries, the system validates the user's eligibility to log time against a specific project, checks for overlapping time entries, and ensures compliance with project billing rules. For active project queries, the system retrieves and displays relevant project details, including assigned team members, deadlines, and progress metrics. The method also includes generating reports and notifications to keep users informed of time tracking deadlines, project updates, and compliance issues. The system integrates with external project management tools to synchronize data and provide a unified view of project status and time allocation. This approach improves accuracy, reduces administrative overhead, and enhances collaboration by providing real-time insights into project progress and resource utilization.
10. The method of claim 6 , said determining the action comprising: determining a first confidence level associated with a first action in the plurality of actions and a second confidence level associated with a second action in the plurality of actions; determining that the first confidence level is greater than the second confidence level; and in response to said determining, selecting the first action as the action.
This invention relates to decision-making systems that evaluate multiple possible actions and select the optimal one based on confidence levels. The problem addressed is the need for automated systems to reliably choose the best action from a set of alternatives when multiple options are available, ensuring accuracy and efficiency in decision-making processes. The method involves analyzing a plurality of potential actions to determine the most suitable one. For each action, a confidence level is calculated, representing the system's certainty that the action is correct or optimal. The confidence levels of at least two actions are compared, and the action with the higher confidence level is selected. This ensures that the system prioritizes the most reliable option, reducing the risk of errors in automated decision-making. The confidence levels may be derived from various factors, such as historical data, real-time inputs, or predictive models. The comparison process ensures that only the highest-confidence action is chosen, improving the system's performance in applications like robotics, autonomous vehicles, or AI-driven decision support. The method enhances reliability by systematically evaluating and selecting the best action based on quantifiable confidence metrics.
11. The method of claim 10 , comprising: when the first confidence level is below a predetermined threshold, asking the user for a confirmation prior to performing the action.
This invention relates to a method for improving the reliability of automated decision-making systems, particularly in scenarios where actions are taken based on analyzed data. The problem addressed is the risk of errors or unintended consequences when automated systems execute actions without sufficient confidence in their decisions. The method involves analyzing data to determine a first confidence level associated with a proposed action. If the confidence level is below a predetermined threshold, the system prompts the user for confirmation before proceeding with the action. This ensures that actions are only taken when the system has high confidence or when a user explicitly approves them, reducing the likelihood of errors. The method may also involve analyzing additional data to determine a second confidence level, which may influence whether the action is performed or further user input is requested. The system may also track user responses to refine future confidence thresholds, improving accuracy over time. This approach balances automation efficiency with user oversight, particularly in critical applications where errors could have significant consequences.
12. The method of claim 10 , comprising: upon receiving a positive feedback in response to selecting the first action, increasing the first confidence level; and upon receiving a negative feedback in response to selecting the first action, decreasing the first confidence level.
This invention relates to adaptive systems that adjust action selection based on user feedback. The problem addressed is the need for systems to dynamically refine their decision-making processes by learning from user interactions. The invention provides a method for updating confidence levels associated with actions in response to user feedback, improving the accuracy and relevance of future action recommendations. The method involves selecting a first action from a set of possible actions based on a first confidence level. The confidence level represents the system's certainty that the action is appropriate for the given context. After the action is selected, the system receives feedback from the user. If the feedback is positive, indicating the action was beneficial or correct, the system increases the first confidence level. Conversely, if the feedback is negative, indicating the action was ineffective or incorrect, the system decreases the first confidence level. This adjustment ensures that future action selections are more aligned with user preferences and requirements. The method may also involve selecting a second action from the set of possible actions based on a second confidence level, which is adjusted similarly in response to feedback. The system may further determine whether the first action is appropriate based on a comparison of the first confidence level to a predefined threshold. If the confidence level meets or exceeds the threshold, the action is selected; otherwise, an alternative action may be chosen. This adaptive feedback mechanism enhances the system's ability to learn and improve over time.
13. The method of claim 6 , said interpreting the natural language request comprising: obtaining a natural language input from the user entered prior to the natural language request; and interpreting the natural language request based on the natural language input entered prior to the natural language request.
This invention relates to natural language processing systems that interpret user requests. The problem addressed is the difficulty in accurately understanding user intent when requests are ambiguous or lack context. The solution involves analyzing prior natural language inputs from the user to improve the interpretation of subsequent requests. The method includes obtaining a natural language input from the user before receiving the actual request. This prior input is used to provide contextual information that helps interpret the later request. For example, if a user previously asked about a specific topic, the system can use that context to better understand a related but ambiguous follow-up question. The system processes the prior input to extract relevant context, such as keywords, topics, or user preferences, and applies this context to refine the interpretation of the new request. This approach enhances accuracy by reducing ambiguity and improving the system's ability to infer user intent based on historical interactions. The method may also involve storing the prior input for future reference, allowing the system to maintain a history of interactions to further refine interpretations over time. This technique is particularly useful in applications like virtual assistants, chatbots, or voice-controlled systems where context is critical for accurate responses. By leveraging prior inputs, the system can provide more relevant and precise responses to user requests.
14. A system comprising: a groupware platform to receive a natural language request from a user and to forward the natural language request to a multiplatform management system; the multiplatform management system to interface with a plurality of disparate platforms and to obtain a plurality of actions, each action in the plurality of actions can be performed by at least one platform in the plurality of disparate platforms, the multiplatform management system to receive the natural language request, to format the natural language request into a formatted natural language request accepted by a natural language processing platform, and to forward the formatted natural language request to the natural language processing platform; the natural language processing platform to receive the formatted natural language request, to identify a user requested action associated with the natural language request, and to forward the identified user requested action to the multiplatform management system; the multiplatform management system to facilitate communication between the plurality of disparate platforms by determining a platform in the plurality of disparate platforms that can perform the user requested action, formatting the user requested action into a formatted user requested action accepted by the platform and sending the formatted user requested action to the platform; and the platform to perform the action.
This system integrates multiple platforms to execute user requests formulated in natural language. The technology addresses the challenge of coordinating actions across disparate platforms that lack interoperability, requiring users to manually navigate different interfaces. The system includes a groupware platform that receives natural language requests from users and forwards them to a multiplatform management system. This management system interfaces with various platforms, each capable of performing specific actions. It formats the natural language request into a structure compatible with a natural language processing platform, which then interprets the request to identify the desired action. The management system determines which platform can execute the action, formats the request accordingly, and sends it to the appropriate platform. The platform then performs the action, enabling seamless execution of user requests across multiple systems without manual intervention. The system enhances efficiency by automating cross-platform task execution through natural language input.
15. The system of claim 14 , comprising: the groupware platform to receive a natural language response from the user and to forward the natural language request to the multiplatform management system; and the multiplatform management system to provide a feedback to the natural language processing platform, wherein the feedback is reinforcing when the natural language response comprises a positive feedback and the feedback is discouraging when the natural language response comprises a negative feedback.
This invention relates to a system for managing interactions between a groupware platform and a multiplatform management system, focusing on natural language processing (NLP) to improve user feedback handling. The system addresses the challenge of effectively processing and responding to user feedback in natural language, ensuring that positive or negative responses influence system behavior in a meaningful way. The groupware platform receives natural language responses from users and forwards these responses to the multiplatform management system. The multiplatform management system then analyzes the feedback and provides a response to the NLP platform. If the user's feedback is positive, the system generates reinforcing feedback, which may include acknowledgment, rewards, or adjustments to improve user experience. Conversely, if the feedback is negative, the system issues discouraging feedback, which could involve corrective actions, warnings, or modifications to address the issue. The system ensures that user interactions are dynamically adjusted based on feedback, enhancing engagement and system performance. The multiplatform management system may also track feedback trends to refine responses over time, ensuring continuous improvement in handling user input. This approach optimizes user satisfaction by adapting to feedback in real-time, making the system more responsive and user-centric.
16. The system of claim 14 , the multiplatform management system comprising: a cloud elastic compute platform to receive a communication in a first programming language to determine a type of the communication, and based on the type of the communication to determine a second platform to which to send the communication; and a polyglot platform to receive the communication in the first programming language and the second platform from the cloud elastic compute platform, to translate the communication from the first programming language associated with a first platform to a second programming language associated with the second platform, and to send the translated communication to the second platform.
This invention relates to a multiplatform management system designed to facilitate communication between different computing platforms using distinct programming languages. The system addresses the challenge of interoperability in heterogeneous computing environments where platforms may use different programming languages, making direct communication difficult. The system includes a cloud elastic compute platform that receives communications in a first programming language and determines the type of communication. Based on this determination, the cloud elastic compute platform identifies a second platform to which the communication should be routed. The system also includes a polyglot platform that receives the communication in the first programming language and the target platform information from the cloud elastic compute platform. The polyglot platform then translates the communication from the first programming language associated with the first platform to a second programming language compatible with the second platform. After translation, the polyglot platform sends the translated communication to the second platform, enabling seamless interaction between platforms that would otherwise be incompatible due to language differences. This approach ensures that communications are accurately routed and translated, improving interoperability in multiplatform environments.
17. The system of claim 16 , the type of communication comprising an image or a text.
A system for processing and analyzing communication data, such as images or text, to extract meaningful information. The system includes a communication interface that receives input data in the form of images or text from various sources. A preprocessing module processes the received data to prepare it for analysis, which may involve noise reduction, normalization, or feature extraction. An analysis module then evaluates the processed data to identify relevant patterns, keywords, or contextual information. The system further includes a storage module for retaining the analyzed data and a user interface for displaying the results to users. The analysis may involve natural language processing for text or computer vision techniques for images, depending on the input type. The system is designed to automate the extraction of insights from communication data, improving efficiency in tasks such as content moderation, sentiment analysis, or data categorization. The system may also integrate with external databases or APIs to enhance its analytical capabilities.
18. The system of claim 14 , the plurality of disparate platforms comprising a plurality of incompatible databases storing information regarding a workplace, or an image analysis platform to analyze an image received from the user.
This invention relates to a system for integrating and analyzing data from multiple disparate platforms in a workplace environment. The system addresses the challenge of managing and extracting insights from fragmented data sources that are often incompatible, such as different databases or image analysis platforms. The system collects and processes information from these varied sources, including workplace-related data and images, to provide a unified and actionable understanding. The image analysis platform specifically processes images received from users, enabling visual data to be incorporated alongside structured workplace data. By integrating these diverse inputs, the system enhances decision-making, automation, and operational efficiency in workplace settings. The system may also include a user interface for interacting with the integrated data, ensuring that users can access and utilize the consolidated information effectively. The overall solution aims to bridge gaps between incompatible data sources, streamline workflows, and improve data-driven decision-making in workplace environments.
19. The system of claim 14 , the groupware platform comprising a user interface receiving a text or a spoken language.
The system involves a groupware platform designed to facilitate collaborative work by processing and managing text or spoken language inputs. The platform includes a user interface that accepts text or spoken language inputs from users, enabling real-time collaboration and communication. The system is configured to process these inputs, which may include natural language commands, queries, or conversational exchanges, and provide relevant responses or actions based on the input. The groupware platform may integrate with other collaborative tools, such as document editing, project management, or communication applications, to enhance productivity and streamline workflows. The system may also include features for translating spoken language into text, analyzing sentiment or intent, and generating automated responses. The platform is designed to support multiple users simultaneously, allowing for seamless interaction and coordination in a shared digital workspace. The system may further include machine learning components to improve accuracy and personalization over time, adapting to user preferences and behaviors. The overall goal is to provide an efficient and intuitive environment for team collaboration, reducing communication barriers and increasing productivity.
20. The system of claim 14 , comprising the groupware platform to: enable a plurality of users to interact by a user interface associated with the groupware platform; receive a user input from the user in the plurality of users; determine whether the user input is directed to the groupware platform; and upon determining that the user input is directed to the groupware platform, forward the user input to the multiplatform management system.
This invention relates to a groupware platform system designed to facilitate collaboration among multiple users. The system addresses the challenge of efficiently managing and routing user inputs within a multiplatform environment, ensuring that interactions intended for the groupware platform are properly processed. The groupware platform enables users to engage through a dedicated user interface, allowing seamless communication and collaboration. When a user input is received, the system determines whether the input is directed to the groupware platform itself or another system. If the input is intended for the groupware platform, it is forwarded to a multiplatform management system for further processing. This ensures that user interactions are correctly routed, improving system efficiency and user experience. The system may also include features for managing user sessions, handling authentication, and integrating with external platforms, enhancing its versatility in collaborative environments. The invention aims to streamline user interactions within groupware systems, reducing errors and improving responsiveness.
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November 24, 2020
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